This paper combines the key aspects of artefact-based systems. DSS and artificial intelligence in a unified approach to solve a typical financial analysis problem within the design science paradigm.
Our proposition is based on the seven design science guidelines. Our proposed “method” artefact is a financial application catering to the investment domain in particular. We present a detailed analysis of stock data from the Indian market for an extended period of 17 years by deploying state-of-the-art algorithms. The use of computational intelligence involving machine and deep learning helps in automatically identifying winning stocks within a value portfolio, that too, on a forward-looking basis.
Our “method” artefact depicts superior results by identifying outperforming stocks, differentiated from the weak ones, within the value portfolio.
This has significant implications for the investing community, particularly the Indian investors. Traditional research in value stocks has shown underwhelming performance in differentiating lucrative stocks from the rest.
